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Research Areas AI coaching Dynamic game theory Human-robot interaction Reinforcement learning Safe embodied AI Trustworthy autonomy

Haimin Hu is an assistant professor of computer science and a member of the Johns Hopkins Data Science and AI Institute, the Laboratory for Computational Sensing and Robotics, and the Institute for Assured Autonomy.

His research focuses on the algorithmic foundations of human-centered autonomy. By integrating dynamic game theory with machine learning and safety-critical control, his work enables deployable, verifiable, and trustworthy systems, from autonomous vehicles to drones and legged robots. Specifically, his research covers the following topics:

  • Uncertainty-aware motion planning: How can robots plan safe and efficient motion by accounting for their evolving uncertainty, as well as their ability to reduce it through future interaction, sensing, communication, and learning?
  • Human-AI co-evolution and co-adaptation: How can embodied AI systems learn from human teammates while helping them refine existing skills and acquire new ones in a safe, personalized manner?
  • Safe human-compatible autonomy: How can autonomous systems ensure prescribed safety while remaining aligned with human values and attuned to human cognitive limitations?
  • Scalable and generalizable strategic decision-making: How can multi-robot systems make safe, coordinated decisions in dynamic, human-populated environments?

Hu has received several awards and recognitions, including being named a 2026 Penn AI Fellow, a 2025 Robotics: Science and Systems Pioneer, a 2025 Cyber-Physical Systems Rising Star, and a 2024 Human-Robot Interaction Pioneer. He has worked closely with industry partners such as the Toyota Research Institute and the Honda Research Institute to develop next-generation human-centered autonomy. Currently, he serves as an Associate Editor for IEEE Robotics and Automation Letters.

Hu received a PhD (2025) and an MA (2022) in electrical and computer engineering from Princeton University, an MSE (2020) in electrical engineering from the University of Pennsylvania, and a BEng (2018) in electronic and information engineering from ShanghaiTech University. From 2025 to 2026, he was a postdoctoral fellow with the Penn Research In Embedded Computing and Integrated Systems Engineering Center and the General Robotics, Automation, Sensing, and Perception Lab at the University of Pennsylvania.